TAILIEUCHUNG - Information Theory, Inference & Learning Algorithms

Information theory and inference, often taught separately, are here united in one entertaining textbook. These topics lie at the heart of many exciting areas of contemporary science and engineering - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics, and cryptography. This textbook introduces theory in tandem with applications. Information theory is taught alongside practical communication systems, such as arithmetic coding for data compression and. | Copyright Cambridge University Press 2003. On-screen viewing permitted. Printing not permitted. http 0521642981 You can buy this book for 30 pounds or 50. See http mackay itila for links. Information Theory Inference and Learning Algorithms David . MacKay gag Cambridge UNIVERSITY PRESS Copyright Cambridge University Press 2003. On-screen viewing permitted. Printing not permitted. http 0521642981 You can buy this book for 30 pounds or 50. See http mackay itila for links. Information Theory Inference and Learning Algorithms David . MacKay mackay@ 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 Cambridge University Press 2003 Version fourth printing March 28 2005 Please send feedback on this book via http mackay itila Version of this book was published by . in September 2003. It will remain viewable on-screen on the above website in postscript djvu and pdf formats. In the second printing version minor typos were corrected and the book design was slightly altered to modify the placement of section numbers. In the third printing version minor typos were corrected and chapter 8 was renamed Dependent random variables instead of Correlated . In the fourth printing version minor typos were corrected. . replace this page with their own page ii. Copyright Cambridge University Press 2003. On-screen viewing permitted. Printing not permitted. http 0521642981 You can buy this book for 30 pounds or 50. See http mackay itila for links. Contents Preface . v 1 Introduction to Information Theory . 3 2 Probability Entropy and Inference. 22 3 More about Inference . 48 I Data Compression . 65 4 The Source Coding Theorem . 67 5 Symbol Codes . 91 6 Stream Codes. 110 7 Codes for Integers . 132 II Noisy-Channel Coding . 137 8 Dependent Random Variables. 138 9 Communication

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